{"id":"W2159452932","doi":"10.1061/9780784412947.108","title":"Climate Change Impacts on Design Storms and Urban Runoff Characteristics","year":2013,"lang":"en","type":"article","venue":"World Environmental and Water Resources Congress 2013","topic":"Climate variability and models","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Downscaling; Environmental science; Precipitation; Watershed; Storm; Climatology; Climate change; Surface runoff; Extreme value theory; Generalized extreme value distribution; Meteorology; Geography; Computer science; Statistics; Mathematics; Geology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005581915,0.000232464,0.0001385765,0.000567429,0.0001427191,0.0003763477,0.0001678306,0.000161424,0.0005450204],"category_scores_gemma":[0.001660276,0.0001413917,0.0003019353,0.0007013739,0.0001842165,0.0003639311,0.0002357797,0.000169386,0.00006585145],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007839163,"about_ca_system_score_gemma":0.0005180923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0236324,"about_ca_topic_score_gemma":0.05047256,"domain_scores_codex":[0.999824,0.00005955412,0.000008618103,0.00003289424,0.00005663547,0.00001838364],"domain_scores_gemma":[0.9994215,0.0002279166,0.0001281028,0.00006104412,0.0001441384,0.00001732079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001061991,0.00004977855,0.291713,0.00002959419,0.0001101717,0.00007923199,0.0000702678,0.6653273,0.003623662,0.001233629,0.0002587699,0.03739849],"study_design_scores_gemma":[0.0000105561,0.00004175084,0.3462687,0.000006367709,0.00002577322,0.00003334908,0.00009068453,0.648296,0.003202835,0.001134127,0.0008692304,0.00002066343],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9668154,0.00006394793,0.03020618,0.00007167103,0.000004827331,0.00002645274,0.000583187,0.00009426624,0.002134192],"genre_scores_gemma":[0.9949558,0.0000383455,0.004475583,0.000006568286,0.000003357453,0.000008003232,0.0003467092,0.00001104953,0.0001546282],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0236324,"threshold_uncertainty_score":0.04698968,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01735223759284784,"score_gpt":0.1940815911793794,"score_spread":0.1767293535865316,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}